We must all accept that science is data and that data are science, and thus provide for, and justify the need for the support of, much-improved data curation. (Hanson, Sugden, & Alberts) 
 
Researchers are producing an unprecedented deluge of data by using new methods and instrumentation. Others may wish to mine these data for new discoveries and innovations. However, research data are not readily available as sharing is common in only a few fields such as astronomy and genomics. Data sharing practices in other fields vary widely. Moreover, research data take many forms, are handled in many ways, using many approaches, and often are difficult to interpret once removed from their initial context. Data sharing is thus a conundrum. Four rationales for sharing data are examined, drawing examples from the sciences, social sciences, and humanities: (1) to reproduce or to verify research, (2) to make results of publicly funded research available to the public, (3) to enable others to ask new questions of extant data, and (4) to advance the state of research and innovation. These rationales differ by the arguments for sharing, by beneficiaries, and by the motivations and incentives of the many stakeholders involved. The challenges are to understand which data might be shared, by whom, with whom, under what conditions, why, and to what effects. Answers will inform data policy and practice. © 2012 Wiley Periodicals, Inc.

科研数据共享的挑战 (The Conundrum of Sharing Research Data)

This paper presents the findings of the Belmont Forum’s survey on Open Data which targeted the global environmental research and data infrastructure community. It highlights users’ perceptions of the term “open data”, expectations of infrastructure functionalities, and barriers and enablers for the sharing of data. A wide range of good practice examples was pointed out by the respondents which demonstrates a substantial uptake of data sharing through e-infrastructures and a further need for enhancement and consolidation. Among all policy responses, funder policies seem to be the most important motivator. This supports the conclusion that stronger mandates will strengthen the case for data sharing.

/pdf/open-data-in-global-environmental-research-the-belmont-forum-oshht912jv.pdf

Open Data in Global Environmental Research: The Belmont Forum's Open Data Survey.

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An Exploratory Sequential Mixed Methods Approach to Understanding Researchers’ Data Management Practices at UVM: Integrated Findings to Develop Research Data Services

Research data curation initiatives must support heterogeneous kinds of projects, data, and metadata. This article examines variability in data and metadata practices using "institutions" as the key theoretical concept. Institutions, in the sense used here, are stable patterns of human behavior that structure, legitimize, or delegitimize actions, relationships, and understandings within particular situations. Based on prior conceptualizations of institutions, a theoretical framework is presented that outlines 5 categories of "institutional carriers" for data practices: a norms and symbols, b intermediaries, c routines, d standards, and e material objects. These institutional carriers are central to understanding how scientific data and metadata practices originate, stabilize, evolve, and transfer. This institutional framework is applied to 3 case studies: the Center for Embedded Networked Sensing CENS, the Long Term Ecological Research LTER network, and the University Corporation for Atmospheric Research UCAR. These cases are used to illustrate how institutional support for data and metadata management are not uniform within a single organization or academic discipline. Instead, broad spectra of institutional configurations for managing data and metadata exist within and across disciplines and organizations.

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Research data and metadata curation as institutional issues

Objectives: The primary objectives of this study are to gauge the various levels of Research Data Service academic libraries provide based on demographic factors, gauging RDS growth since 2011, and what obstacles may prevent expansion or growth of services. Methods: Survey of academic institutions through stratified random sample of ACRL library directors across the U.S. and Canada. Frequencies and chi-square analysis were applied, with some responses grouped into broader categories for analysis. Results: Minimal to no change for what services were offered between survey years, and interviews with library directors were conducted to help explain this lack of change. Conclusion: Further analysis is forthcoming for a librarians study to help explain possible discrepancies in organizational objectives and librarian sentiments of RDS. Correspondence: Carol Tenopir: ctenopir@utk.edu

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Research Data Services in Academic Libraries: Data Intensive Roles for the Future?

Academic librarians are increasingly engaging in data curation by providing infrastructure (e.g., institutional repositories) and offering services (e.g., data management plan consultations) to support the management of research data on their campuses. Efforts to develop these resources may benefit from a greater understanding of disciplinary differences in research data management needs. After conducting a survey of data management practices and perspectives at our research university, we categorized faculty members into four research domains—arts and humanities, social sciences, medical sciences, and basic sciences—and analyzed variations in their patterns of survey responses. We found statistically significant differences among the four research domains for nearly every survey item, revealing important disciplinary distinctions in data management actions, attitudes, and interest in support services. Serious consideration of both the similarities and dissimilarities among disciplines will help guide academic librarians and other data curation professionals in developing a range of data-management services that can be tailored to the unique needs of different scholarly researchers.

/pdf/disciplinary-differences-in-faculty-research-data-management-37yggjkt3r.pdf

Disciplinary Differences in Faculty Research Data Management Practices and Perspectives

Academic libraries are increasingly engaging in data curation by providing infrastructure and services to support the management of research data on their campus. Efforts to develop these resources can benefit from a greater understanding of the social factors that affect how researchers manage their data during and after their research projects. In particular, the age or amount of experience of researchers is often thought to be an important factor influencing their viewpoints on research data sharing and preservation. In this study, we categorized faculty members who responded to our campus-wide survey on research data management into four ranks—professor, associate professor, assistant professor, and non-tenure track— and analyzed differences in their patterns of survey responses. We found statistically significant differences among faculty ranks in familiarity with funding agency requirements for data management plans, reasons that might prevent data sharing, and interest in potential research data services. These findings reveal key distinctions among different ranks of faculty members in their outlook toward research data management, which can help guide academic librarians and data curation professionals to develop research data services that are tailored to the unique needs of specific populations of researchers.

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Differences among Faculty Ranks in Views on Research Data Management

Faculty practices and perspectives on Research Data Management.

INTRODUCTION The support and curation of research data underlying theses and dissertations are an opportunity for institutions to enhance their ETD collections. This article describes a pilot data archiving service that leverages Emory University’s existing Electronic Theses and Dissertations (ETDs) program. DESCRIPTION OF PROGRAM This pilot service tested the appropriateness of Dataverse, a data repository, as a data archiving and access solution for Emory University using research data identified in Emory University’s ETD repository, developed the legal documents necessary for a full implementation of Dataverse on campus, and expanded outreach efforts to meet the research data needs of graduate students. This article also situates the pilot service within the context of Emory Libraries and explains how it relates to other library efforts currently underway. NEXT STEPS The pilot project team plans to seek permission from alumni whose data were included in the pilot to make them available publicly in Dataverse, and the team will revise the ETD license agreement to allow this type of use. The team will also automate the ingest of supplemental ETD research data into the data repository where possible and create a workshop series for students who are creating research data as part of their theses or dissertations.

https://iastatedigitalpress.com/jlsc/article/12754/galley/12442/download/

Making Student Research Data Discoverable: A Pilot Program Using Dataverse

EDITOR'S SUMMARY



Three data specialists reviewed their experiences learning about and applying the Inter-university Consortium for Political and Social Research (ICPSR) processes and tools for curating research data. A small virtual community discussed curation theories on data acquisitions, review, processing, metadata and dissemination and shared progress implementing the ICPSR workflows and tools. Curators at Duke University, dealing with data on political donors, found processing obstacles from incomplete and mismatched data and faced confidentiality questions. At Emory University, gaps in coded data on home schooling practices revealed problems arising from lack of preplanning for long-term archiving and research and the need to clarify data needs for later re-use. By applying ICPSR processes, curators at UCLA's Social Sciences Data Archive were able to improve their workflow and understand the work necessary for open archiving. All participants gained from the opportunity to practice ICPSR curation practices, realized the resource demands and saw the value librarians can provide by consulting with faculty on data management and preservation.

https://asistdl.onlinelibrary.wiley.com/doi/pdf/10.1002/bult.2014.1720400610

Jennifer Doty

Papers

Disciplinary Differences in Faculty Research Data Management Practices and Perspectives

Differences among Faculty Ranks in Views on Research Data Management

Faculty practices and perspectives on Research Data Management.

Making Student Research Data Discoverable: A Pilot Program Using Dataverse

Learning to curate